Hey guys, I’m the cofounder of a tech startup focused on providing free AI services.
We’ve developed a pretty cool app that offers AI services like image generation, code generation, image captioning, and more for free.
We’re sort of like a Swiss Army knife of generative and analytical AI.
We’ve released a new feature called AAIA(Ask AI Anything), which is capable of answering all types of questions, even requests to generate literature (fantasy, folklore, drama, fiction, fable, etc). It’s sort of like chat-gpt.
We’d appreciate it if you could try it out and let us know your thoughts: https://apps.apple.com/us/app/bright-eye/id1593932475
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There are incredible applications built using AI.
It is definitely a trend that the world should not ignore.
We started to maintain a collection of cool ai projects in Github: https://github.com/ai-collection/ai-collection
Our mission is to increase reach and visibility for these awesome projects!
It is updated daily and we hope that with the help of the community, it will be a great source for discovering AI applications.
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This post is co-written with Jennifer Bergstrom, Sr. Technical Director, ParsonsX. Parsons Corporation (NYSE:PSN) is a leading disruptive technology company in critical infrastructure, national defense, space, intelligence, and security markets providing solutions across the globe to help make the world safer, healthier, and more connected. Parsons provides services and capabilities across cybersecurity, missile defense, space ground […]
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This post is co-written by Ramdev Wudali and Kiran Mantripragada from Thomson Reuters. In 1992, Thomson Reuters (TR) released its first AI legal research service, WIN (Westlaw Is Natural), an innovation at the time, as most search engines only supported Boolean terms and connectors. Since then, TR has achieved many more milestones as its AI […]
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This blog post is co-written with Chaoyang He and Salman Avestimehr from FedML. Analyzing real-world healthcare and life sciences (HCLS) data poses several practical challenges, such as distributed data silos, lack of sufficient data at a single site for rare events, regulatory guidelines that prohibit data sharing, infrastructure requirement, and cost incurred in creating a […]
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This blog post is co-written with Chaoyang He and Salman Avestimehr from FedML. Analyzing real-world healthcare and life sciences (HCLS) data poses several practical challenges, such as distributed data silos, lack of sufficient data at any single site for rare events, regulatory guidelines that prohibit data sharing, infrastructure requirement, and cost incurred in creating a […]
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These skills might not be visiable but they are important for ML and DL
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One of the biggest AI discoveries over the past year has been the importance of human feedback for building next-gen LLMs — but I still see a lot of confusion around how RLHF works at a fundamental level.
I wrote a blog to get into the details here: https://www.surgehq.ai/blog/introduction-to-reinforcement-learning-with-human-feedback-rlhf-series-part-1
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The Open Deep Learning Toolkit for Robotics version 2.0 was just released! This new version of the toolkit includes several improvements, such as new tools for object detection, efficient continual inference, tracking, emotion estimation and high-resolution pose estimation. Furthermore, this version includes a refined ROS interface, along with support for ROS2.
You can download it here: https://github.com/opendr-eu/opendr
We look forward to receiving your feedback, bug reports, and suggestions for improvements!
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Have a look at this medium article:
https://pub.towardsai.net/how-to-create-a-python-package-for-fetching-weather-data-b17614627f30
And the corresponding repository:
https://github.com/stavrostheocharis/weather_data_retriever
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New fellows are working on health records, robot control, pandemic preparedness, brain injuries, and more.
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This post was co-authored with Mark Lott, Distinguished Technical Architect, Salesforce, Inc. Enterprises that operate globally are experiencing challenges sourcing customer support professionals with multi-lingual experience. This process can be cost-prohibitive and difficult to scale, leading many enterprises to only support English for chats. Using human interpreters for translation support is expensive, and infeasible since […]
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This is guest post by Andy Whittle, Principal Platform Engineer – Application & Reliability Frameworks at The Very Group. At The Very Group, which operates digital retailer Very, security is a top priority in handling data for millions of customers. Part of how The Very Group secures and tracks business operations is through activity logging […]
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Using a pretrained AI model from NVIDIA, startup Evozyne created two proteins with significant potential in healthcare and clean energy. A joint paper released today describes the process and the biological building blocks it produced. One aims to cure a congenital disease, another is designed to consume carbon dioxide to reduce global warming. Initial results Read article >
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GFN Thursday kicks each weekend off with new games and updates straight from the cloud. This week adds more games from publisher THQ Nordic to the GeForce NOW library, as part seven total additions. Members can gear up to play these new titles the ultimate way with the upcoming release of the new Ultimate membership, Read article >
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The global retail industry has a $100 billion problem. “Shrinkage” — the loss of goods due to theft, damage and misplacement — significantly crimps retailers’ profits. An estimated 65% of shrinkage is due to theft, according to the National Retail Federation’s 2022 Retail Security Survey, conducted in partnership with the Loss Prevention Research Council. And Read article >
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Hey guys, I’m the cofounder of a tech startup focused on providing free AI services.
We’ve developed a pretty cool app that offers AI services like image generation, code generation, image captioning, and more for free. We’re sort of like a Swiss Army knife of generative and analytical AI.
In light of the chatgpt bug going on rn, check us out and stay in touch with us:
https://apps.apple.com/us/app/bright-eye/id1593932475
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In the nearest future, tens of thousands of self-driving cars may be on the roads. Big companies like BMW and Tesla continue to invest.
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Advancement in AI has shaken multiple grounds at the same time. What does it mean for designers?
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This post is co-authored by Marios Skevofylakas, Jason Ramchandani and Haykaz Aramyan from Refinitiv, An LSEG Business. Financial service providers often need to identify relevant news, analyze it, extract insights, and take actions in real time, like trading specific instruments (such as commodities, shares, funds) based on additional information or context of the news item. […]
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I am trying to implement a custom PettingZoo environment, and a shared policy with Stable Baselines 3. I am running into trouble with the action spaces not being compatible, since PettingZoo has started using gymnasium instead of gym. Does anyone know if these libraries no longer work together, and perhaps if there is a work-around?
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3D and animation extraordinaire CG Geek completed an ambitious design challenge this week In the NVIDIA Studio — building a massive, sci-fi-inspired 3D world in only three days
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OpenAI researchers collaborated with Georgetown University’s Center for Security and Emerging Technology and the Stanford Internet Observatory to investigate how large language models might be misused for disinformation purposes. The collaboration included an October 2021 workshop bringing together 30 disinformation researchers, machine learning experts, and policy analysts, and
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MIT researchers developed and studied a customized AI training program for users with varied backgrounds, which could be delivered across large organizations.
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Story here: https://www.bloomberg.com/news/articles/2023-01-10/microsoft-weighs-10-billion-chatgpt-investment-semafor-says?srnd=premium
Unpaywalled: https://archive.ph/XOOlg
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I have a set of ~100 topic categories, and I want to determine which are semantically close to a text input.
I've found several implementations, but I know some (LDA) are already obsolete. OpenAI's text-embedding-ada-002 model just came out so I'm wondering if that's the best option now.
Other topic modeling implementations:
Multi-Class Text Classification with Doc2Vec & Logistic Regression
Build taxonomy-based contextual targeting using AWS Media Intelligence and Hugging Face BERT
Topic Modeling with BERTopic
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The demand for web and app development is rising as there are significant improvements in the field of technology every year. More and more people are establishing careers in the field of development as a result of advancements in technologies and frameworks. As a result, the data from Statista says that by 2024, there will… Read More »Flexible Engagement Model to Hire Full-Stack Developers: A 2023 Guide
The post Flexible Engagement Model to Hire Full-Stack Developers: A 2023 Guide appeared first on Data Science Central.
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AI is at the heart of humanity’s most transformative innovations — from developing COVID vaccines at unprecedented speeds and diagnosing cancer to powering autonomous vehicles and understanding climate change. Virtually every industry will benefit from adopting AI, but the technology has become more resource intensive as neural networks have increased in complexity. To avoid placing Read article >
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Amazon SageMaker is a fully managed machine learning (ML) service. With SageMaker, data scientists and developers can quickly and easily build and train ML models, and then directly deploy them into a production-ready hosted environment. It provides an integrated Jupyter authoring notebook instance for easy access to your data sources for exploration and analysis, so […]
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If you’ve had the opportunity to build a search application for unstructured data (i.e., wiki, informational web sites, self-service help pages, internal documentation, etc.) using open source or commercial-off-the-shelf search engines, then you’re probably familiar with the inherent accuracy challenges involved in getting relevant search results. The intended meaning of both query and document can […]
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Improve Tortoise TTS by 30% inference speed, and packaged it up as a hosted API that charges per-second. All code is open-sourced: https://github.com/metavoicexyz/tortoise-tts-modal-api, https://github.com/metavoicexyz/tortoise-tts
It can be used via a UI on: https://tts.themetavoice.xyz
There are more details here: https://twitter.com/vatsal\_aggarwal/status/1612536547248836608?s=20
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This is the first episode of a new podcast on machine learning featuring Maarten Grootendorst.
Maarten Grootendorst: BERTopic, Data Science, Psychology | Learning from Machine Learning #1
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Introduction:
Continue reading on Becoming Human: Artificial Intelligence Magazine »
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This is part 3 of a three-part series on the Economics of Ethics. In Part I of the Economics of Ethic series, we talked about economics as a framework for the creation and distribution of society value. In Part II, we discussed the difference between financial and economic measures, the role of laws and regulations… Read More »Economics of Ethics: Is Ethics Ultimately an Economics Conversation? Part III
The post Economics of Ethics: Is Ethics Ultimately an Economics Conversation? Part III appeared first on Data Science Central.
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Back before he retired, Naval War College professor and contributor to The Atlantic Tom Nichols published a 2017 book called The Death of Expertise. Those who claim their own facts or knowledge without supporting evidence, he noted, have become more and more prominent in online conversation we’ve been having. And the noisiest and most prone… Read More »Data science and the death of (all but narrow) AI expertise in 2023
The post Data science and the death of (all but narrow) AI expertise in 2023 appeared first on Data Science Central.
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Machine learning (ML) applications are complex to deploy and often require the ability to hyper-scale, and have ultra-low latency requirements and stringent cost budgets. Use cases such as fraud detection, product recommendations, and traffic prediction are examples where milliseconds matter and are critical for business success. Strict service level agreements (SLAs) need to be met, […]
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I made a short video comparing Google to Perplexity.ai. Let me know what you think! https://youtu.be/qQi_sTmKOyk
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📄 This is a transcript from AI Test Kitchen.
👉 aitestkitchen.withgoogle.com
🗣 It records an interaction with LaMDA, an AI language model.
🛠 LaMDA is an early stage technology. It may generate inaccurate/inappropriate information.
Demo:
Imagine It v0.01
User: Imagine I'm at a Web browser and I want to use the best search engine
Model: You're at this great search engine called Duckduckgo! The colors are a vibrant green and blue. There's a little duck mascot in the corner of the page. And the sound of the search results are soft and pleasant.
User: why is it called Duckduckgo?
Model: The creators liked the idea of a search engine that didn't collect or store any of your personal data, so that's why they named it Duckduckgo!
User: what are some good things …
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Hi,
I want to play with AI and translating of audio digital data into zeros and ones and then encoding them/translating into DNA sequence (A,D,T,N) . I read a few yrs back that massive attack did that with their album: https://newatlas.com/massive-attack-mezzanine-dna-eth-zurich/54324/.
Does anyone know anything about this?
Yes, thanks, cheers
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I want to generate a smooth image-morphing video of Anime characters' faces with around 40 Custom Images. Something similar to this (images used in this is not custom images)
Can anyone guide me through the steps of how to achieve these results with StyleGan2? Or is there any better alternative?
I'm totally new to this please help!
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Hi guys,
I have made a video on YouTube here where I cover why the Adam optimizer may fail to converge on some simple optimization problems and how AMSgrad aims to solve this issue .
I hope it may be of use to some of you out there. As always, feedback is more than welcomed! :)
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Hi ! Wrote an article about AI/ML in the Anti-Money laundering industry !
https://medium.com/@melmasset/ai-and-data-in-finance-the-role-of-machine-learning-in-anti-money-laundering-1d4dd6f5bacd
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Hey guys just did my first test with deforum for a dnb music, what you think? still trying to learn the best way to make it reactive with the strength schedule..
https://youtu.be/SuGQ8xmKmGI
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after using chatgpt for a couple of weeks, ive realised how powerful it can be to help me do my job.
it's so good at what it does that the only way to not get left behind is to learn how to use the tool effectively, so i did some reasearch, some of the following are some useful tips.
this free ebook is a great introduction to understanding how to utilise chatgpt effectively for what you want it to do:
The Art of ChatGPT Prompting: A Guide to Crafting Clear and Effective Prompts
a very powerful feature of chatGPT is to configure into a mode with the "Act as" hack
i found this chrome extension that comes with a few predefined modes,
https://github.com/f/awesome-chatgpt-prompts
i ended up not boring with the extension since all the instructions for each profile are in this file:
https://github.com/f/awesome-chatgpt-prompts/blob/main/prompts.csv
ive been taking these examples and augmenting them to my needs
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The other day I came up with this interesting video made by Tensorflow and Françoise Beaufay (research scientist at Google). This article…
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Behind the scene — with scratch mathematics
Continue reading on Becoming Human: Artificial Intelligence Magazine »
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Out-of-copyright books only of course.
Hi, I was wondering if I could fine tune a GPT3 model to take a book, likely in html, markdown, or plain text, and convert it to SSML. In order to do that, I would need a bunch of SSML files already hand made, and fine tune a model based on them. Then I've got some code to split that up and do formatting: pandoc, csplit, and then I could use aws polly or one of the others to do real good text to speech.
Anyone have a dataset?
References:
https://cloud.google.com/text-to-speech/docs/ssml
https://christiantietze.de/posts/2019/12/markdown-split-by-chapter/
https://pandoc.org/demos.html
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Designing and building an intelligent conversational interface is very different than building a traditional application or website. These best practices for Amazon Lex interaction models will help you develop those new skills as you design and optimize your next bot.
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This three-part series demonstrates how to use graph neural networks (GNNs) and Amazon Neptune to generate movie recommendations using the IMDb and Box Office Mojo Movies/TV/OTT licensable data package, which provides a wide range of entertainment metadata, including over 1 billion user ratings; credits for more than 11 million cast and crew members; 9 million […]
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The recently published IDC MarketScape: Asia/Pacific (Excluding Japan) AI Life-Cycle Software Tools and Platforms 2022 Vendor Assessment positions AWS in the Leaders category. This was the first and only APEJ-specific analyst evaluation focused on AI life-cycle software from IDC. The vendors evaluated for this MarketScape offer various software tools needed to support end-to-end machine learning […]
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This post is co-written by Hesham Fahim from Thomson Reuters. Thomson Reuters (TR) is one of the world’s most trusted information organizations for businesses and professionals. It provides companies with the intelligence, technology, and human expertise they need to find trusted answers, enabling them to make better decisions more quickly. TR’s customers span across the […]
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https://www.anandtech.com/show/18721/ces-2023-amd-instinct-mi300-data-center-apu-silicon-in-hand-146b-transistors-shipping-h223
I wonder if this is the beginning of dissolution of NVIDIA's monopoly on AI.
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Computer engineering has come a long way from merely being a curriculum major to a key credential for your AI portfolio. Artificial engineering is a role that commands huge skill and expertise in the realm of technology. Unsurprisingly, the demand for their services outstrips the supply. The industry is oozing with valuable companies with diversified… Read More »AI Engineer: Learn About The Role And Skills Needed For Success In 2023
The post AI Engineer: Learn About The Role And Skills Needed For Success In 2023 appeared first on Data Science Central.
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The role-playing game “On the Plane” simulates xenophobia to foster greater understanding and reflection via virtual experiences.
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Autonomous vehicle (AV) technology is heading to the mainstream. The NVIDIA DRIVE ecosystem showcased significant milestones toward widespread intelligent transportation at CES. Growth is occurring in vehicle deployment plans as well as AI solutions integrating further into the car. Foxconn joined the NVIDIA DRIVE ecosystem. The world’s largest technology manufacturer will produce electronic control units Read article >
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GFN Thursday rings in the new year with a recap of the biggest cloud gaming news from CES 2023: the GeForce NOW Ultimate membership. Powered by the latest NVIDIA GPU technology, Ultimate members can play their favorite PC games at performance never before available from the cloud. Plus, with a new year comes new games. Read article >
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https://www.youtube.com/watch?v=DUi7v0eIPz4&lc=Ugxuw-xuUSYvVnbfjrV4AaABAg&ab_channel=ScaleAI
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At AWS we released Fortuna, a library for Uncertainty Quantification. Fortuna supports conformal prediction, Bayesian inference methods and more.
Try it out! GitHub stars are very welcome!!! ⭐⭐⭐
Github repo: https://github.com/awslabs/fortuna
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Hi,
As part of Huggingface whisper finetuning event I created a demo where you can:
Download youtube video with a given URL
2. Watch downloaded video in the first video component
3. Run automatic speech recognition on the video using Whisper models from ggerganov https://github.com/ggerganov/whisper.cpp
4. Translate the recognized transcriptions to 26 languages supported by deepL
Download generated subtitle files in .srt and .vtt formats
6. Watch the video in another video component with added subtitles
You can test it from here
--> https://huggingface.co/spaces/RASMUS/Whisper-youtube-crosslingual-subtitles <--
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Editor’s note: This is part of a series profiling people advancing science with high performance computing. Ryan Coffee makes movies of molecules. Their impacts are huge. The senior scientist at the SLAC National Accelerator Laboratory (above) says these visualizations could unlock the secrets of photosynthesis. They’ve already shown how sunlight can cause skin cancer. Long Read article >
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When NVIDIA co-founder Chris Malachowsky approached University of Florida Provost Joe Glover with the offer of an AI supercomputer, he couldn’t have predicted the transformative impact it would have on the university. In just a short time, UF has become one of the top public colleges in the U.S. and developed a groundbreaking neural network Read article >
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A new method can produce a hundredfold increase in light emissions from a type of electron-photon coupling, which is key to electron microscopes and other technologies.
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2023 UPDATE! Just published a book with 1337 use cases and around 4000 examples.
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Choose your Programming Language
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Robots celebrate holidays?
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MAgent2 is the maintained fork of the environments in https://github.com/geek-ai/MAgent, which previously were housed in PettingZoo itself but as of a few months ago was broken off into it's own project. You can check it out here: https://magent2.farama.org/ / https://github.com/Farama-Foundation/magent2
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RIFFUSION is an app for real-time music generation with stable diffusion. Riffusion is a latent text-to-image diffusion model capable of generating spectrogram images given any text input. These spectrograms can be converted into audio clips.The model was created by Seth Forsgren and Hayk Martiros as a hobby project. It employs some clever tricks by fine tuning stable diffusion on spectogram images and interploation in latent space for creating smooth transitions in generated audio clips
I have created a video explaining the concepts behind RIFFUSION. Do checkout the video: https://youtu.be/hGrtZ9rXwWk
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CLARIFICATION: NOT DAN SUI BUT I AM PROMOTING MY ARTICLE
I decided to purchase and take a gander at this new frontier of AI Art monetization.
Check it out here and let me know your thoughts! Article
Dan Sui or u/KoSuiFish famous for beautiful life-like Waifu's released a gumroad course
With works such as
- NSFW (very nsfw)
- SFW
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Social media is one of the most widely accessible online platforms people use to share their personal views and opinions and express their feelings with a few show-offs of their social life with their friends. Now it is also used for business promotions and commercial activities, to engage with users and target more customers. On… Read More »How does social media content moderation work in the United States?
The post How does social media content moderation work in the United States? appeared first on Data Science Central.
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Powerful new GeForce RTX GPUs, a new generation of hyper-efficient laptops and new Omniverse capabilities and partnerships across the automotive industry were highlights of a news-packed address ahead of this week’s CES trade show in Las Vegas. “AI will define the future of computing and this has influenced much of what we’re covering today,” said Read article >
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The latest release of NVIDIA Omniverse Enterprise, available now, brings increased performance, generational leaps in real-time RTX ray and path tracing, and streamlined workflows to help teams build connected 3D pipelines, and develop and operate large-scale, physically accurate, virtual 3D worlds like never before. Artists, designers, engineers and developers can benefit from various enhancements across Read article >
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AI is extending further into the vehicle as autonomous-driving technology becomes more prevalent. With the NVIDIA DRIVE platform, automakers can design and implement intelligent interior features to continuously surprise and delight customers. It all begins with the compute architecture. The recently introduced NVIDIA DRIVE Thor platform unifies traditionally distributed functions in vehicles — including digital Read article >
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Building state-of-the-art factories requires a state-of-the art planning system. Mercedes-Benz announced at CES that it is taking the next step in digitizing its production process, using the NVIDIA Omniverse platform to design and plan manufacturing and assembly facilities. By tapping into NVIDIA AI and metaverse technologies, the automaker can create feedback loops to reduce waste, Read article >
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Autonomous and electric vehicles are making personal transportation safer and more sustainable — as well as more entertaining. At CES today, NVIDIA announced that the NVIDIA GeForce NOW cloud gaming service will be coming to cars, with no special equipment needed. Hyundai Motor Group, BYD and Polestar — already members of the NVIDIA DRIVE ecosystem Read article >
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The future of content creation was on full display today during NVIDIA’s virtual special address at CES. Fueled by powerful NVIDIA RTX technology and backed by the NVIDIA Studio platform for creators, a creative revolution is underway as a wave of 2D artists moves to 3D, video workflows move to real time and AI tools help artists create content faster.
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Demand for intelligent robots is growing as more industries embrace automation to address supply chain challenges and labor force shortages. The installed base of industrial and commercial robots will grow more than 6.4x — from 3.1 million in 2020 to 20 million in 2030, according to ABI Research. Developing, validating and deploying these new AI-based Read article >
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Whether creating realistic digital humans that can express raw emotion or building immersive virtual worlds, those in the design, engineering, creative and other industries across the globe are reaching new heights through 3D workflows. Animators, creators and developers can use new AI-powered tools to reimagine 3D environments, simulations and the metaverse — the 3D evolution Read article >
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Hello, community!
I invite you to take a look at the live coding tutorial video on Diffusion Models
Link to the video
Content covered:
- Theoretical background
- Implementation of forward diffusion process
- Implementation of the training loop
- Overfitting to one batch
- Implementation of the reverse diffusion process
- Training on CIFAR10 dataset (with class label conditioning)
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If you’re reading this, chances are you’re curious about what Chat GPT (Generative Pre-trained Transformer) is and how it works. Maybe…
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The insurance sector is adopting new technologies at a rapid pace, with many companies implementing new technologies to improve their…
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We are a leading chatbot & enterprise software development services provider in India. We provide end to end RPA services along with AI…
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Hi,
I would like to make my own footage on some topics, but to make it more interesting to viewers, I would love to add additional video content like royalty free or some clips from YouTube.
Is there any tool that can do that for me?
So far I've found only Pictory.ai that has some of those features.
Thanks in advance
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Worth having a look at. Some great and innovative ideas.
https://www.youtube.com/watch?v=ulYbnHyg1no
Anyone has any different ideas or out of the box thinking for using AI to make some money on the side? Let me know.
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Those looking to join the ranks of AI trailblazers or chart a new course in their careers need look no further. At NVIDIA’s latest GTC conference, industry leaders in a panel called “5 Paths to a Career in AI” shared tips and insights on how to make a mark in this rapidly evolving field. Representing Read article >
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This is part 2 of a three-part series on the Economics of Ethics. In Part I of the Economics of Ethic series, we talked about economics as a framework for the creation and distribution of society value. With AI’s ability to learn and adapt billions of times faster than humans, society must get the definition… Read More »Economics of Ethics: Is Ethics Ultimately an Economics Conversation? Part II
The post Economics of Ethics: Is Ethics Ultimately an Economics Conversation? Part II appeared first on Data Science Central.
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Title says it all. Im experimenting with a bi-weekly news segment that's intended for keeping people up to date on events in AI from a high level.
I just published Episode 2 today and would like feedback on areas for improvement.
https://youtu.be/kQk7f6gsPDE
Thanks in advance!
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Irrational numbers such as π may have been the first ones used to create perfect randomness and strong cryptographic systems. They were also among the first ones to be dismissed, long ago. Since then, they were never revisited and are completely abandoned. Binary digits of numbers such as π are remarkable at mimicking randomness. Indeed… Read More »New Military-grade Random Bit Sequences Based on Irrational Numbers and Fast Computations
The post New Military-grade Random Bit Sequences Based on Irrational Numbers and Fast Computations appeared first on Data Science Central.
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I'm trying to understand how I can use COMET to evaluate translation models https://github.com/Unbabel/COMET ?
I don't really understand how it was trained the meaning of the outputed values ? https://unbabel.github.io/COMET/html/faqs.html#which-comet-model-should-i-use
Thanks for your help
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The way we hire has changed dramatically over the last 10 years. Technology has been a major driver of these changes, especially through…
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thinking the unthinkable., Machine Learning
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Hey Guy's, so I tried to make a NeuralNetwork for the dataset of Quickdraw, but I always get the error: TypeError: can't convert np.ndarray of type numpy.object_. The only supported types are: float64, float32, float16, complex64, complex128, int64, int32, int16, int8, uint8, and bool.
How can i fix this, more detail on StackOverflow: https://stackoverflow.com/questions/74962055/typeerror-cant-convert-np-ndarray-of-type-numpy-object
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Stephen Tong, aka Funky Boy, has always loved music and photography. He’s now transferring the skills developed over the years as a music producer — shooting time lapses, creating audio tracks and more — to a new passion of his: 3D content creation.
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Last year, we announced the general availability of RStudio on Amazon SageMaker, the industry’s first fully managed RStudio Workbench integrated development environment (IDE) in the cloud. You can quickly launch the familiar RStudio IDE and dial up and down the underlying compute resources without interrupting your work, making it easy to build machine learning (ML) […]
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The last decade of the Industry 4.0 revolution has shown the value and importance of machine learning (ML) across verticals and environments, with more impact on manufacturing than possibly any other application. Organizations implementing a more automated, reliable, and cost-effective Operational Technology (OT) strategy have led the way, recognizing the benefits of ML in predicting […]
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NVIDIA executives will share some of the company’s latest innovations Tuesday, Jan. 3, at 8 a.m. Pacific time ahead of this year’s CES trade show in Las Vegas. Jeff Fisher, senior vice president for gaming products, will be joined by Deepu Talla, vice president of embedded and edge computing, Stephanie Johnson, vice president of consumer Read article >
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One of tech’s top talk shows, the NVIDIA AI Podcast has attracted more than 3.6 million listens to date from folks who want to hear the latest in machine learning. Its 180+ installments so far have included interviews with luminaries like Kai-Fu Lee and explored how AI is advancing everything from monitoring endangered rhinos to Read article >
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Recently I got interested in GAN and learned how to convert face images into Disney/Pixar style (high level idea is at https://www.justinpinkney.com/making-toonify/).
Inspired by the success of levelsio in multiple AI projects, I built my own avatar-generating service: https://toonlens.com/ .
Would appreciate any feedback you have.
Thank you!
Kenny
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In recent years, we have seen a significant shift in the way businesses operate and interact with their customers. With the rise of…
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Hey everyone!
Joe and I are students at Stanford, and we finally got a breakthrough on our side project.
We call it:
ChatBCG: Generative AI for Slides ✨
or: Text-to-PowerPoint
(Hope it will replace consultants one day :D)
Check out our launch Tweet for more info:
https://twitter.com/SilasAlberti/status/1608037989623414791
Do you have any feedback? We would really appreciate it :)
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Hi guys!
Just sharing that I just published a new learning environment for reinforcement learning agents to learn policies from pixels. The Wave Defense Learning Environment is useful for debugging new implementations and algorithms the image-based settings (a decent algorithm should solve the environment).
Also, see the baselines repository for the Wave Defense environment to see some RL training results.
Feel free to ⭐star⭐ the repository if you like it or use it, and let me know what you think!
Thank you! 😁
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Six companies with innovative products built using the NVIDIA Jetson edge AI platform will leave CES, one of the world’s largest consumer technology trade shows, as big winners next week. The CES Innovation Awards each year honor outstanding design and engineering in more than two dozen categories of consumer technology products. The companies to be Read article >
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Simulating revolutions - ChatGPT and symbolic simulations, an article.
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I was building a YOLOv5 object detection model, and was looking into researching synthetic methods like GANs to increase the size of my training set in an unsupervised manner.
Ik few-shot GANs can be used to "hallucinate" images and labels for a classification task, but how can they be extended to hallucinate images and labels in YOLO format (basically lists out each bounding box and class)?
Is there some way that I can train a GAN on images / YOLO labels, and get it to hallucinate more images / labels?
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Artist Zhelong Xu, aka Uncle Light, brought to life Blood Moon — a 3D masterpiece combining imagination, craftsmanship and art styles from the Chinese Bronze Age — along with Kirin, a symbol of hope and good fortune, using NVIDIA technologies.
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These explainers will give you the scoop on the latest tech developments from AI models to green computing.
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This is part 1 of a three-part series on the Economics of Ethics. Here’s the problem with the data and AI ethics conversation – if we can’t measure it, then we can’t monitor it, judge it, or change it. We must find a way to transparently instrument and measure ethics. And that’ll become even more… Read More »Economics of Ethics: Is Ethics Ultimately an Economics Conversation? Part I
The post Economics of Ethics: Is Ethics Ultimately an Economics Conversation? Part I appeared first on Data Science Central.
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Can you help me sign this petition? https://chng.it/Z6Nf64Q7vc
Thanks a lot.
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Tools for getting the job done in machine learning
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Introduction
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- Images:
NightCafe Creator Limited to 10 images / day.
Midjourney (Discord server) Limited
- Questions: AISEO
- Music: SOUNDRAW
Do you know of any other tools?
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AI Weirdness: the strange side of machine learning
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Well here's the story
https://docs.google.com/document/d/1u5Am2j5koDBzss8kf5iJySG2dJ0Z1rhwa2hdTqSVeQ8/edit?usp=drivesdk
Just remember this story was created by ten different AI each sentence created by a different one. I did give the first AI that created the first sentence a little bit of backstory about both characters. This was an experiment to see if different AI could work together to create something.
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Github Link: https://github.com/kpthedev/stable-karlo
I made stable-karlo, an app that combines Kakaobrain's Karlo image generation model with Stable-Diffusion 2.1 in a nice webUI.
Recently, Kakaobrain released Karlo, their own image generating diffusion model which uses OpenAI's unCLIP architecture. The model is great at understanding text and relationships, but it only outputs 256x256 pixel images. I had the idea to combine Karlo with the new Stable-Diffusion v2 upscaler to get large images and the results are very promising.
Please check out the Github and share your thoughts!
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Customer service interactions often contain personally identifiable information (PII) such as names, phone numbers, and dates of birth. As organizations incorporate machine learning (ML) and analytics into their applications, using this data can provide insights on how to create more seamless customer experiences. However, the presence of PII information often restricts the use of this […]
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Intro & source code: https://github.com/houkensjtu/taichi-hackathon-akinasan
The circuit of an ordinary RC toy car is modified so that Jetson Nano can control the movement of the car through GPIO port. Of course, we need to use motor drive controller here, because the upper limit of the output current of Jetson Nano is not enough to drive the car motor directly.
The convolution neural network (CNN) is implemented using Taichi programming language.
The road data was collected, then classified and labeled, and finally used in the training of CNN models.
The pre-trained model is imported into Jetson Nano and the action prediction made for the images captured during driving.
Demo:
https://reddit.com/link/zshrlv/video/pcm3f6id3f7a1/player
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Built on recent advances in machine learning, the model predicts how well individuals will produce and comprehend sentences.
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Launched at AWS re:Invent 2021, Amazon SageMaker Ground Truth Plus helps you create high-quality training datasets by removing the undifferentiated heavy lifting associated with building data labeling applications and managing the labeling workforce. All you do is share data along with labeling requirements, and Ground Truth Plus sets up and manages your data labeling workflow […]
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This holiday season, feast on the bounty of food-themed stories NVIDIA Blog readers gobbled up in 2022. Startups in the retail industry — and particularly in quick-service restaurants — are using NVIDIA AI and robotics technology to make it easier to order food in drive-thrus, find beverages on store shelves and have meals delivered. They’re Read article >
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In a moment of pure serendipity, Lah Yileh Lee and Xinting Lee, a pair of talented singers who often stream their performances online, found themselves performing in a public square in Taipei when NVIDIA founder and CEO Jensen Huang happened upon them. Huang couldn’t resist joining in, cheering on their serenade as they recorded Lady Read article >
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Gear up for some festive fun this GFN Thursday with some of the GeForce NOW community’s top picks of games to play during the holidays, as well as a new title joining the GeForce NOW library this week. And, following the recent update that enabled Ubisoft Connect account syncing with GeForce NOW, select Ubisoft+ Multi-Access Read article >
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Game characters BUT in anime neural network...
I created pictures of game characters in a social network that makes anime out of any pictures, look, and if it's not difficult to rate here, well, or on YouTube
https://youtu.be/ZDdzG333x9Q
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Legendary footballers BUT in anime...
I created pictures of legendary footballers in a social network that makes anime out of any pictures, look, and if it's not difficult to rate here, well, or on YouTube
https://youtu.be/kqGBQ_0BXc0
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Whisperer
A tool to make audio-text datasets automatically for your ML Projects. Two weeks ago, I shared an early draft of a project based on the newly released OpenAI's Whisper. Today I'm sharing the finished version of Whisperer, which adds diarization, with same-speaker detection across multiple audio files.
Key Features:
Automatic Speaker Diarization
Automatic Speaker Identification
e.g: same speakers across audio files
Automatic Transcription
Forces Gaussian Distributions of the dataset see notebook
Modular and Configurable
EDIT:
Live on twitch if anyone has any questions.
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BLIP from Salesforce is now available on Hugging Face transformers!
Here is a list of cool applications you can build on top of it: https://twitter.com/younesbelkada/status/1605489647395540992
With (I think) most interesting application being building image-captioning APIs and Stable Diffusion-related applications (generate image-text datasets to fine-tune Stable Diffusion on it & image to music app)
Any other thing you have in mind that can be built using BLIP?
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Posted by Jinsung Yoon and Sercan O. Arik, Research Scientists, Google Research, Cloud AI Team
Analysis of Electronic Health Records (EHR) has a tremendous potential for enhancing patient care, quantitatively measuring performance of clinical practices, and facilitating clinical research. Statistical estimation and machine learning (ML) models trained on EHR data can be used to predict the probability of various diseases (such as diabetes), track patient wellness, and predict how patients respond to specific drugs. For such models, researchers and practitioners need access to EHR data. However, it can be challenging to leverage EHR data while ensuring data privacy and conforming to patient confidentiality regulations (such as HIPAA).
Conventional methods to anonymize data (e.g., de-id…
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Auto-encoders are an unsupervised learning technique using neural networks to learn representations.
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On the well-known iris dataset, we will perform the neural network operation here without writing a single line of Python code. Sounds…
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Introduction:
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Linear regression is one of the main algorithms that you must master as a data scientist, you will learn how to build your first model…
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Amazon Kendra is a highly accurate and simple-to-use intelligent search service powered by machine learning (ML). Amazon Kendra offers a suite of data source connectors to simplify the process of ingesting and indexing your content, wherever it resides. Valuable data in organizations is stored in both structured and unstructured repositories. An enterprise search solution should […]
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Today, companies are establishing feature stores to provide a central repository to scale ML development across business units and data science teams. As feature data grows in size and complexity, data scientists need to be able to efficiently query these feature stores to extract datasets for experimentation, model training, and batch scoring. Amazon SageMaker Feature […]
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Amazon Kendra is a highly accurate and simple-to-use intelligent search service powered by machine learning (ML). Amazon Kendra offers a suite of data source connectors to simplify the process of ingesting and indexing your content, wherever it resides. Valuable data in organizations is stored in both structured and unstructured repositories. An enterprise search solution should […]
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All of us recycle. Or, at least, all of us should. Now, AI is joining the effort. On the latest episode of the NVIDIA AI Podcast, host Noah Kravitz spoke with JD Ambadti, founder and CEO of EverestLabs, developer of RecycleOS, the first AI-enabled operating system for recycling. The company reports that an average of Read article >
The post Doing the Best They Can: EverestLabs Ensures Fewer Recyclables Go to Landfills appeared first on NVIDIA Blog.
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Announcements Highlighting Our Contributors This week is DSC’s final issue of DSC Weekly in 2022. With the conclusion of the year, we’re highlighting two of our top contributors’ and their articles from the last year. These articles are chosen for their high-quality, informative nature and attention to detail. Alan Morrison posts articles with critical thought… Read More »DSC Weekly 20 December 2022 – Highlighting Our Contributors Part 2
The post DSC Weekly 20 December 2022 – Highlighting Our Contributors Part 2 appeared first on Data Science Central.
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There are many articles that point to the risks of AI. Indeed, these risks are real, but also many of these articles are based on scaremongering and sensationalism. If we take a medium to long-term view, we definitely need to think differently about the risks of AI. Here is why: a) We do not take… Read More »Why we need to think differently about AI risks in the medium to long term
The post Why we need to think differently about AI risks in the medium to long term appeared first on Data Science Central.
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Hi everyone, my lab has recently made Foresight - in short, it is a GPT-3 like language model that can simulate a patient's future (forecast disorders, medications, procedures, symptoms, ...). It was trained and tested on two large hospitals in UK covering both physical and mental health. Any feedback is much appreciated (Twitter or here).
Paper: arxiv
Demo: foresight
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Abstract: The adoption of pre-trained language models in task-oriented dialogue systems has resulted in significant enhancements of their text generation abilities. However, these architectures are slow to use because of the large number of trainable parameters and can sometimes fail to generate diverse responses. To address these limitations, we propose two models with auxiliary tasks for response selection - (1) distinguishing distractors from ground truth responses and (2) distinguishing synthetic responses from ground truth labels. They achieve state-of-the-art results on the MultiWOZ 2.1 dataset with combined scores of 107.5 and 108.3 and outperform a baseline with three times more parameters. We publish reproducible code and checkpoints and discuss the effects of applying auxiliary tasks to T5-based architectures.
Project available on GitHub: https://github.com/radi-cho/RSTOD
Our paper was presented at https://www.icnlsp.org/. Publication in process.
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https://thriveml.com
most job boards i've seen include technical roles (e.g., ML engineer, data scientist), so I wanted to make one that includes non-technical positions in sales, customer support, etc. i think we'll see a lot of startups (and jobs) in this space in the coming year.
lmk what you think! happy to add more companies.
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This three-part series demonstrates how to use graph neural networks (GNNs) and Amazon Neptune to generate movie recommendations using the IMDb and Box Office Mojo Movies/TV/OTT licensable data package, which provides a wide range of entertainment metadata, including over 1 billion user ratings; credits for more than 11 million cast and crew members; 9 million […]
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The IMDb and Box Office Mojo Movies/TV/OTT licensable data package provides a wide range of entertainment metadata, including over 1 billion user ratings; credits for more than 11 million cast and crew members; 9 million movie, TV, and entertainment titles; and global box office reporting data from more than 60 countries. Many AWS media and […]
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The last few years have seen a tremendous paradigm shift in how institutional asset managers source and integrate multiple data sources into their investment process. With frequent shifts in risk correlations, unexpected sources of volatility, and increasing competition from passive strategies, asset managers are employing a broader set of third-party data sources to gain a […]
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3D artist Edward McEvenue shares his imaginative, holiday-themed short film "The Great Candy Inquisition" this week In the NVIDIA Studio.
The post 3D Artist Edward McEvenue Animates Holiday Cheer This Week ‘In the NVIDIA Studio’ appeared first on NVIDIA Blog.
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At big conferences it is fun to get some human labels, because it is super high quality and high density. At neurips 2022 I wanted to study how humans use language to "fix" or "correct" an existing artifact. The current big models, such as stable diffusion, are generative from descriptions -- It is impossible to have an output image, and describe precisely how one might want to change it to improve it.
To quote from the blog post:
Imagine describing a task for your friend to perform. It is unlikely they’ll get it right on the first try. Often, additional communications are needed to modify and improve what is being done so far.
At Neurips 2022, I conducted a small study to get a sense of the following:
Q1: How valuable is the modification process?
Q2: Are the languages of modification and description different?
Check out the blog (5min read) for the full report: https://evanthebouncy.medium.com/the-language-of-modifications-17fac974c1ef
TL;DR: We find that modification is both valuable and distinct from descriptive language.
have a good one!
--evan
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I would have thought that, in order to avoid any train/test contamination, we need to take the parameters from the training set PCA and use them to transform the test set, as oppose to just combining train and test and performing PCA at once. Does anyone have any idea how this is done in sklearn? I found this post which offers a solution, could anyone perhaps confirm that this is the correct way to do this? Cheers.
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https://nounsummaries.substack.com/p/meet-the-nouns-dao-ai-noc-lite-at
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Today we announce the general availability of Renate, an open-source Python library for automatic model retraining. The library provides continual learning algorithms able to incrementally train a neural network as more data becomes available. By open-sourcing Renate, we would like to create a venue where practitioners working on real-world machine learning systems and researchers interested […]
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Deploying high-quality, trained machine learning (ML) models to perform either batch or real-time inference is a critical piece of bringing value to customers. However, the ML experimentation process can be tedious—there are a lot of approaches requiring a significant amount of time to implement. That’s why pre-trained ML models like the ones provided in the PyTorch […]
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Hey guys wanted to show you my app which offers a convenient frontend to use Whisper for transcriptions with Libretranslate to power automatic translations
Code is all open-source here: https://github.com/mayeaux/generate-subtitles
Also running an instance that you can use for free at https://freesubtitles.ai
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Is this possible?
Train transformers on a quantum computer to model them for classical computing purposes such as running quantum cross validated regression locally?
https://discuss.huggingface.co/t/quantum-transformer/28044
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Hi everyone. Have you ever read a book written 100% by AI?
Now you got the chance. I started to work on my Sci-Fi novel using Artificial Intelligence. Together, we wrote an exciting book and made fantastic illustrations for it.
It's called Beyond The Horizon, it takes place in the year 2120. The main character, Jenna, a young astronaut is sent on a mission to explore a new planet.
Here is the link for the first chapter (pdf version): https://drive.google.com/file/d/1eaY3EOVW4LucsEfcNvugknxbkti9xaqD/view?usp=share_link
Let me know what you think!
Thanks,
Tom
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Businesses collect a huge volume of data daily from various sources like ERMs, e-commerce platforms, supply chains, and many other internal and external sources. In making use of this data, we make use of data-driven decisions, organizations need business intelligence (BI). What is business intelligence? It refers to a mix of business analytics, data mining,… Read More »Application and Benefits of Business Intelligence in Manufacturing
The post Application and Benefits of Business Intelligence in Manufacturing appeared first on Data Science Central.
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Hi all,
We are training a distilBART model to summarize podcasts.
We want to be able to properly document the process, and how each decision affects the model.
So far that has included using rouge scores to determine the performance. If there are any other things you think we should do, please let me know.
But back to the question from the title:
For some reason, I just can not figure out how to control the training results. I want to see training- and validation loss after every epoch, but it keeps either putting it at some weird interval like here (code), or not at all like here (code).
Will appreciate any help and general criticism of what we are doing!
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I'd like to use one of those engine's for Q/A
I see some nice tools out there like nshepherd and happytransformer, but neither of them use squad, but I do see some GPT-Neo squad models out there (for ex with GPT-NeoX)
https://www.forefront.ai/blog-posts/how-to-fine-tune-gpt-neox
submitted by /u/Thistleknot
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I have a AI model embodiment project. POC is pretty far along. I need help to accelerate it to the finish:
https://www.notion.so/Mind-Machine-Learning-2707060e25ec43978884b5e718c0c0d8
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submitted by /u/QubaHQ
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I have a AI model embodiment project. I need help to accelerate it:
https://www.notion.so/Mind-Machine-Learning-2707060e25ec43978884b5e718c0c0d8
submitted by /u/bhartsb
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( 53
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submitted by /u/gwern
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Hey guys! I was fascinated by the concept of the seed_rl when it first came out because I believe that it could accelerate the training speed in local single machine environment. But I found that the official repo is recently archived and no longer maintains.. So I’m looking for alternatives which I can use seed_rl type distributed RL. Ray(or Rllib) is the most using drl librarys, but it doesn’t seems like using the seed_rl style. Anyone can recommend distributed RL librarys for it, or good for research and for lot’s of code modification? Is RLLib worth to use in single local machine training despite those cons? Thank you!!
submitted by /u/jinPrelude
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Foundation models are large deep learning models trained on a vast quantity of data at scale. They can be further fine-tuned to perform a variety of downstream tasks and form the core backbone of enabling several AI applications. The most prominent category is large-language models (LLM), including auto-regressive models such as GPT variants trained to complete […]
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submitted by /u/palsh7
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Listen to the podcast episode with Nicklas Hansen from UC San Diego where we discuss adapting reinforcement learning policies during deployment, why algorithms don't drive research progress, and much more!
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submitted by /u/Mk_Makanaki
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Hello everyone,
I wanted to share a new video I just released on YouTube here called "Adversarial Discriminative Domain Adaptation (ADDA) Paper Explained." It's a deep dive into the concepts and techniques of ADDA, which is a powerful method for adapting machine learning models to new domains. If you're interested in machine learning and domain adaptation, I think you'll really enjoy it.
Thanks for considering giving it a watch, and I hope you find it helpful! As always, feedback is extremely welcomed!
submitted by /u/Personal-Trainer-541
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submitted by /u/LordPewPew777
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Today, we’re happy to announce updates to our Amazon SageMaker Experiments capability of Amazon SageMaker that lets you organize, track, compare and evaluate machine learning (ML) experiments and model versions from any integrated development environment (IDE) using the SageMaker Python SDK or boto3, including local Jupyter Notebooks. Machine learning (ML) is an iterative process. When solving […]
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Proper estimation of predictive uncertainty is fundamental in applications that involve critical decisions. Uncertainty can be used to assess the reliability of model predictions, trigger human intervention, or decide whether a model can be safely deployed in the wild. We introduce Fortuna, an open-source library for uncertainty quantification. Fortuna provides calibration methods, such as conformal […]
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Amazon SageMaker Training Managed Warm Pools gives you the flexibility to opt in to reuse and hold on to the underlying infrastructure for a user-defined period of time. This is done while also maintaining the benefit of passing the undifferentiated heavy lifting of managing compute instances in to Amazon SageMaker Model Training. In this post, […]
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In an increasingly data-centric world, enterprises must focus on gathering both valuable physical information and generating the information that they need but can’t easily capture. Data access, regulation, and compliance are an increasing source of friction for innovation in analytics and artificial intelligence (AI). For highly regulated sectors such as Financial Services, Healthcare, Life Sciences, […]
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Developing and training successful machine learning (ML) fraud models requires access to large amounts of high-quality data. Sourcing this data is challenging because available datasets are sometimes not large enough or sufficiently unbiased to usefully train the ML model and may require significant cost and time. Regulation and privacy requirements further prevent data use or […]
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Listen to the podcast episode with Nicklas Hansen from UC San Diego where we discuss adapting reinforcement learning policies during deployment, why algorithms don't drive research progress, and much more!
submitted by /u/thejashGI
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submitted by /u/OpenDILab
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A comparative analysis of DL techniques ⚖️
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And how to use them effectively anyway
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There’s no denying that the Internet of Things (IoT) is here to stay. It has changed how we live, work and play, making our lives more…
( 13
min )
Hello everyone,
I wanted to share a new video I just released on YouTube here called "Adversarial Discriminative Domain Adaptation (ADDA) Paper Explained." It's a deep dive into the concepts and techniques of ADDA, which is a powerful method for adapting machine learning models to new domains. If you're interested in machine learning and domain adaptation, I think you'll really enjoy it.
Thanks for considering giving it a watch, and I hope you find it helpful! As always, feedback is extremely welcomed!
submitted by /u/Personal-Trainer-541
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submitted by /u/nickb
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Data for All by John K. Thompson covers data in the most holistic sense. For someone that is not involved in data science, defining the term data can be difficult. If data science is the study of data, what exactly is being studied? Thompson starts at the beginning when defining a term that has increased… Read More »Taking Control of Your Online Presence with Data for All
The post Taking Control of Your Online Presence with Data for All appeared first on Data Science Central.
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But the harm from a discriminatory AI system can be minimized if the advice it delivers is properly framed, an MIT team has shown.
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A national initiative in semiconductors provides a once-in-a-generation opportunity to energize manufacturing in the U.S. The CHIPS and Science Act includes an $13 billion R&D investment in the chip industry. Done right, it’s a recipe for bringing advanced manufacturing techniques to every industry and cultivating a highly skilled workforce. The semiconductor industry uses the most Read article >
The post Accelerated Computing, AI and Digital Twins: A Recipe for US Manufacturing Leadership appeared first on NVIDIA Blog.
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To make transportation safer, autonomous vehicles (AVs) must have processes and underlying systems that meet the highest standards. NVIDIA DRIVE OS is the operating system for in-vehicle accelerated computing powered by the NVIDIA DRIVE platform. DRIVE OS 5.2 is now functional safety-certified by TÜV SÜD, one of the most experienced and rigorous assessment bodies in Read article >
The post Safe Travels: NVIDIA DRIVE OS Receives Premier Safety Certification appeared first on NVIDIA Blog.
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https://youtu.be/0fEG0ClkIdo
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We are thrilled to announce the availability of the LightOn Lyra-fr foundation model for customers using Amazon SageMaker. LightOn is a leader in building foundation models specializing in European languages. Lyra-fr is a state-of-the-art French language model that can be used to build conversational AI, copywriting tools, text classifiers, semantic search, and more. You can […]
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While the weather outside may or may not be frightful this holiday season, new games on GeForce NOW each week make every GFN Thursday delightful. It doesn’t matter whether you’re on the naughty or nice list. With over 1,400 titles streaming from the cloud, there’s something for everyone to play across nearly all of their Read article >
The post Have a Holly, Jolly Holiday Streaming Top Titles on GeForce NOW appeared first on NVIDIA Blog.
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Sponsored Post Attend the Data Science Symposium 2022 on November 8 The Center for Business Analytics at the University of Cincinnati will present its annual Data Science Symposium 2022 on November 8. This all day in-person event will have three featured speakers and two tech talk tracks with four concurrent presentations in each track. The […]
The post Attend the Data Science Symposium 2022, November 8 in Cincinnati appeared first on Machine Learning Mastery.
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